一个简单的方法,利用指数模型来弥补化学氧气需求测量的度,使用UV-VIS光谱学
Hongliang Wang1, Houkui Xiang1, Tongqiang Xiong1
1School of Automation, Hubei University of Science and Technology, Xianning, China.
Frontiers in microbiology
|July 26, 2023
概括
这项研究引入了一个指数模型,使用紫外线光谱仪准确测量水中的化学氧需求 (COD). 该方法有效地弥补了度,大大提高了环境监测的检测精度.
科学领域:
- 环境科学 环境科学
- 分析化学 分析化学
- 频谱学是一种光谱学.
背景情况:
- 紫外可见 (UV-vis) 吸收光谱仪可以实时检测化学氧气需求 (COD).
- 精度受度和UV波长中有机污染物的共同吸收限制.
- 度干扰需要准确的补偿来实现可靠的COD测量.
研究的目的:
- 开发和验证一种可靠的方法来弥补COD确定UV-VIS光谱分析中的度.
- 为了提高COD检测在水样本中的准确性.
主要方法:
- 开发了一个指数模型,以根据其可见吸收率来预测和减去度的紫外线吸收率.
- 部分最小平方 (PLS) 用于从补偿光谱中预测COD度.
- 该模型的性能使用合成和天然废水样本进行了评估.
主要成果:
- 与未经处理的光谱相比,指数模型显著减少了COD预测的根平均平方误差 (RMSE) 从29.9降至9.51.
- 拟议的模型优于现有的方法,如兰伯特-比尔定律 (RMSE=12.53) 和多重分散集群方法 (RMSE=79.34).
- 该模型证明了对天然水样本的适用性,在可见光谱范围中显示一致性.
结论:
- 开发的指数模型为UV对COD分析中的度补偿提供了简单有效的解决方案.
- 这种方法提高了在具有挑战性的水矩阵中COD测量的准确性.
- 该方法适用于实时环境监测和有机污染物早期预警系统.
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